SoroushVahidi/scidocs huggingface dataset:
Infants’ Metaphysics: The Case of Numerical Identity
(1996)

Adults conceptualize the world in terms of enduring physical objects. Sortal concepts provide conditions of individuation (establishing the boundaries of objects) and numerical identity (establishing whether an object is the same one as one encountered at some other time). In the adult conceptual system, there are two roughly hierarchical levels of object sortals. Most general is the sortal bounded physical object itself, for which spatiotemporal properties provide the criteria for individuation and identity. More specific sortals, such as dog or car, rely on additional types of properties to provide criteria for individuation and identity. We conjecture that young infants might represent only the general sortal, object, and construct more specific sortals later (the Object-first Hypothesis). This is closely related to Bower's (1974) conjecture that infants use spatiotemporal information to trace identity before they use property information. Five studies using the visual habituation paradigm were conducted to address the Object-first Hypothesis. In these studies, 10-month-old infants were able to use spatiotemporal information but failed to use property/kind information to set up representations of numerically distinct individuals, thus providing empirical evidence for the Object-first Hypothesis. Finally, infants succeed at object individuation in terms of more specific sortals by 12 months. The relation between success at our task and early noun comprehension is discussed.
The Google effect in doctoral theses
(2012)

It is often said that successive generations of researchers face an increasing educational burden due to knowledge accumulation. On the other hand, technological advancement over time can improve the productivity of researchers and even change their cognitive processes. This paper presents a longitudinal study (2004–2011) of citation behavior in doctoral theses at the Massachusetts Institute of Technology’s Department of Electrical Engineering and Computer Science. It is found that the number of references cited has increased over the years. At the same time, there has been a decrease in the length of time in the doctoral program and a relative constancy in the culture of the department. This suggests that students are more productive in facing an increased knowledge burden, and indeed seem to encode prior literature as transactive memory to a greater extent, as evidenced by the greater use of older literature.
W-Band Large-Scale High-Gain Planar Integrated Antenna Array
(2014)

This communication presents a 32 × 32 high-gain patch array antenna fed by the substrate integrated waveguide (SIW) structure at W-band. The array antenna consists of two layers to achieve a compact topology, which allows for mass production using a standard PCB fabrication process. The wideband feeding network is placed in the bottom layer while the radiating patches are on the top layer. This configuration also resolves the trade-off between gain and bandwidth of conventional SIW array antennas. Measured gain of the 32 × 32 antenna array is within the range 28.81-29.97 dBi in the working bandwidth of 91-97 GHz. Measured impedance bandwidth covers the same frequency band for . The cross-polarization of the antenna array is less than 40 dB at the beam direction. Good agreement between the simulated and measured results validates our design.
Position and Orientation Estimation Through Millimeter-Wave MIMO in 5G Systems
(2018)

Millimeter-wave (mm-wave) signals and large antenna arrays are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are well-known, their potential advantages for accurate positioning are largely undiscovered. We derive the Cramér-Rao bound (CRB) on position and rotation angle estimation uncertainty from mm-wave signals from a single transmitter, in the presence of scatterers. We also present a novel two-stage algorithm for position and rotation angle estimation that attains the CRB for average to high signal-to-noise ratio. The algorithm is based on multiple measurement vectors matching pursuit for coarse estimation, followed by a refinement stage based on the space-alternating generalized expectation maximization algorithm. We find that accurate position and rotation angle estimation is possible using signals from a single transmitter, in either line-of-sight, non-line-of-sight, or obstructed-line-of-sight conditions.
Enhancing the TED-LIUM Corpus with Selected Data for Language Modeling and More TED Talks
(2014)

In this paper, we present improvements made to the TED-LIUM corpus we released in 2012. These enhancements fall into two categories. First, we describe how we filtered publicly available monolingual data and used it to estimate well-suited language models (LMs), using open-source tools. Then, we describe the process of selection we applied to new acoustic data from TED talks, providing additions to our previously released corpus. Finally, we report some experiments we made around these improvements.
Blockchain challenges and opportunities: a survey
(2018)

Copyright © 2017 Inderscience Enterprises Ltd. 2 Blockchain has numerous benefits such as decentralization, persistency, anonymity and auditability. There is a wide spectrum of blockchain applications ranging from cryptocurrency, financial services, risk management, Internet of Things to public and social services. Although a number of studies focus on using the blockchain technology in various application aspects, there is no comprehensive survey on the blockchain technology in both technological and application perspectives. To fill this gap, we conduct a comprehensive survey on the blockchain technology. In particular, this paper gives the blockchain taxonomy, introduces typical blockchain consensus algorithms, reviews blockchain applications and discusses technical challenges as well as recent advances in tackling the challenges. Moreover, this paper also points out the future directions in the blockchain technology.
Detecting and discriminating behavioural anomalies
(2011)

This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex temporal dynamics and correlations among multiple objects’ behaviours. Specifically, we decompose a complex behaviour pattern according to its temporal characteristics or spatial-temporal visual contexts. The decomposed behaviour is then modelled using a cascade of Dynamic Bayesian Networks (CasDBNs). In contrast to existing standalone models, the proposed behaviour decomposition and cascade modelling offers distinct advantage in simplicity for complex behaviour modelling. Importantly, the decomposition and cascade structure map naturally to the structure of complex behaviour, allowing for a more effective detection of subtle anomalies in surveillance videos. Comparative experiments using both indoor and outdoor data are carried out to demonstrate that, in addition to the novel capability of discriminating different types of anomalies, the proposed framework outperforms existing methods in detecting durational anomalies in complex behaviours and subtle anomalies that are difficult to detect when objects are viewed in isolation. & 2010 Elsevier Ltd. All rights reserved.
Mobile Virtual Network Admission Control and Resource Allocation for Wireless Network Virtualization: A Robust Optimization Approach
(2014)

Wireless network virtualization is a promising technology in next generation wireless networks. In this paper, motivated by the experience of user equipment (UE) admission control in traditional wireless networks, we propose a novel concept of mobile virtual network (MVN) admission control for wireless virtualization. By limiting the number of MVNs embedded in the physical network, MVN admission control can effectively guarantee quality of service (QoS) experienced by users of MVNs and maximize the utilization of the physical networks at the same time. Specifically, we propose a two-stage MVN embedding mechanism that can decouple short-term physical resource allocation from long-term admission control and resource leasing. With recent advances in robust optimization, we formulate the MVN admission control problem as a robust optimization problem. Both the long-term admission control and short- term resource allocation problems are transformed to convex problems, which can be solved efficiently. Simulation results are presented to show the effectiveness of the proposed scheme.
A novel framework for SMS spam filtering
(2012)

A novel framework for SMS spam filtering is introduced in this paper to prevent mobile phone users from unsolicited SMS messages. The framework makes use of two distinct feature selection approaches based on information gain and chi-square metrics to find out discriminative features representing SMS messages. The discriminative feature subsets are then employed in two different Bayesian-based classifiers, so that SMS messages are categorized as either spam or legitimate. Moreover, the paper introduces a real-time mobile application for Android™ based mobile phones utilizing the proposed spam filtering scheme, as well. Hence, SMS spam messages are silently filtered out without disturbing phone users. Effectiveness of the filtering framework is evaluated on a large SMS message collection including legitimate and spam messages. Following the evaluation, remarkably accurate classification results are obtained for both spam and legitimate messages.
Forecasting stock price directional movements using technical indicators: Investigating window size effects on one-step-ahead forecasting
(2014)

Accurate forecasting of directional changes in stock prices is important for algorithmic trading and investment management. Technical analysis has been successfully used in financial forecasting and recently researchers have explored the optimization of parameters for technical indicators. This study investigates the relationship between the window size used for calculating technical indicators and the accuracy of one-step-ahead (variable steps) forecasting. The directions of the future price movements are predicted using technical analysis and machine learning algorithms. Results show a correlation between window size and forecasting step size for the Support Vector Machines approach but not for the other approaches.
Scene Graph Generation by Belief RNNs
(2017)

Understanding and describing the scene beyond an image has great value. It is a 1 step forward from recognizing individual objects and their relationships in isolation. 2 In addition, Scene graph is a crucial step towards a deeper understanding of a visual 3 scene. We present a method in an end-to-end model that given an image generates 4 a scene graph including nodes that corresponds to the objects in the image and 5 an edges corresponds to relationship between objects. Our main contribution is 6 introducing a novel deep structure prediction module Belief RNNs that performs 7 learning on a large graphs in a very efficient and generic way. 8
A new Design Criteria for Hash-Functions
(2010)

The most common way of constructing a hash function (e.g., SHA-1) is to iterate a compression function on the input message. The compression function is usually designed from scratch or made out of a block-cipher. In this paper, we introduce a new security notion for hash-functions, stronger than collision-resistance. Under this notion, the arbitrary length hash function H must behave as a random oracle when the fixed-length building block is viewed as an ideal primitive. This enables to eliminate all possible generic attacks against iterative hash-functions. In this paper, we show that the current design principle behind hash functions such as SHA-1 and MD5 — the (strengthened) Merkle-Damg̊ard transformation — does not satisfy this security notion. We provide several constructions that provably satisfy this notion; those new constructions introduce minimal changes to the plain Merkle-Damg̊ard construction and are easily implementable in practice. This paper is a modified version of a paper to appear at Crypto 2005.
Ordinary magic. Resilience processes in development.
(2001)

The study of resilience in development has overturned many negative assumptions and deficit-focused models about children growing up under the threat of disadvantage and adversity. The most surprising conclusion emerging from studies of these children is the ordinariness of resilience. An examination of converging findings from variable-focused and person-focused investigations of these phenomena suggests that resilience is common and that it usually arises from the normative functions of human adaptational systems, with the greatest threats to human development being those that compromise these protective systems. The conclusion that resilience is made of ordinary rather than extraordinary processes offers a more positive outlook on human development and adaptation, as well as direction for policy and practice aimed at enhancing the development of children at risk for problems and psychopathology.
An automated framework for generating variable-accuracy battery models from datasheet information
(2013)

Models based on an electrical circuit equivalent have become the most popular choice for modeling the behavior of batteries, thanks to their ease of co-simulation with other parts of a digital system. Such circuit models are actually model templates: the specific values of their electrical elements must be derived by the analysis of the specific battery devices to be modeled. This process requires either to measure the battery characteristics or to derive them from the datasheet. In the latter case, however, very often not all information are available and the model fitting becomes then unfeasible.
 In this paper we present a methodology for deriving, in a semi-automatic way, circuit equivalent battery models solely from data available in a battery datasheet. In order to account for the different amount of information available, we introduce the concept of "level" of a model, so that models with different accuracy can be derived depending on the available data. The methodology requires only minimal intervention by the designer and it automatically generates MATLAB models once the required data for the corresponding model level are transcribed from the datasheet.
 Simulation results show that our methodology allows to accurately reconstruct the information reported in the datasheet as well as to derive missing ones.
Spatial Reference in Linguistic Human-Robot Interaction: Iterative, Empirically Supported Development of a Model of Projective Relations
(2006)

The aim of our research is to enable spontaneous and efficient spatial reference to objects in human-robot interaction situations. This paper presents the iterative, empirically based design of a robotic system that uses a computational model for identifying objects on the basis of a range of spatial reference systems. The efficiency of the system is evaluated by two successive empirical studies involving uninformed users. The linguistic analysis points to the striking variability in speakers’ spontaneous strategies and preferences, and it motivates a number of modifications of the computational model.
Mobile Media Use, Multitasking and Distractibility
(2012)

Portable media devices are ubiquitous and their use has become a core component of many people’s daily experience, but to what effect? In this paper, the authors review research on the ways in which media use and multitasking relate to distraction, distractibility and impulsivity. They review recent research on the effects of media multitasking on driving, walking, work, and academic performance. The authors discuss earlier research concerning the nature of media’s impact on attention and review cognitive and neuropsychological findings on the effects of divided attention. Research provides clear evidence that mobile media use is distracting, with consequences for safety, efficiency and learning. Greater use of media is correlated with higher levels of trait impulsivity and distractibility, but the direction of causality has not been established. Individuals may become more skilled at media multitasking over time, but intervention is currently required to improve the safe and effective use of mobile media. DOI: 10.4018/ijcbpl.2012070102 16 International Journal of Cyber Behavior, Psychology and Learning, 2(3), 15-29, July-September 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. and neuropsychological research on the effects of divided attention. Finally, we explore how high levels of media multitasking might alter our general responses to experience in ways that are marked by changes in distractibility and impulsivity. THE DISTRACTING EFFECTS OF MULTITASKING WITH MOBILE MEDIA
Multileaved Comparisons for Fast Online Evaluation
(2014)

Evaluation methods for information retrieval systems come in three types: offline evaluation, using static data sets annotated for relevance by human judges; user studies, usually conducted in a lab-based setting; and online evaluation, using implicit signals such as clicks from actual users. For the latter, preferences between rankers are typically inferred from implicit signals via interleaved comparison methods, which combine a pair of rankings and display the result to the user. We propose a new approach to online evaluation called multileaved comparisons that is useful in the prevalent case where designers are interested in the relative performance of more than two rankers. Rather than combining only a pair of rankings, multileaved comparisons combine an arbitrary number of rankings. The resulting user clicks then give feedback about how all these rankings compare to each other. We propose two specific multileaved comparison methods. The first, called team draft multileave, is an extension of team draft interleave. The second, called optimized multileave, is an extension of optimized interleave and is designed to handle cases where a large number of rankers must be multileaved. We present experimental results that demonstrate that both team draft multileave and optimized multileave can accurately determine all pairwise preferences among a set of rankers using far less data than the interleaving methods that they extend.
A tensorized logic programming language for large-scale data
(2019)

We introduce a new logic programming language T-PRISM based on tensor embeddings. Our embedding scheme is a modification of the distribution semantics in PRISM, one of the state-of-the-art probabilistic logic programming languages, by replacing distribution functions with multidimensional arrays, i.e., tensors. T-PRISM consists of two parts: logic programming part and numerical computation part. The former provides flexible and interpretable modeling at the level of first order logic, and the latter part provides scalable computation utilizing parallelization and hardware acceleration with GPUs. Combing these two parts provides a remarkably wide range of high-level declarative modeling from symbolic reasoning to deep learning. To embody this programming language, we also introduce a new semantics, termed tensorized semantics, which combines the traditional least model semantics in logic programming with the embeddings of tensors. In T-PRISM, we first derive a set of equations related to tensors from a given program using logical inference, i.e., Prolog execution in a symbolic space and then solve the derived equations in a continuous space by TensorFlow. Using our preliminary implementation of T-PRISM, we have successfully dealt with a wide range of modeling. We have succeeded in dealing with real large-scale data in the declarative modeling. This paper presents a DistMult model for knowledge graphs using the FB15k and WN18 datasets.
X-band microstrip narrowband BPF composed of split ring resonator
(2016)

The paper deals with the development of X-band microstrip narrowband bandpass filter (BPF) composed of split ring resonator (SRR). The proposed filter is designed on a grounded 0.508mm thick Roger RT/Duroid® 5880 dielectric substrate with the dimension of 25mm length and 20mm width. Some parametric studies to achieve an optimum design of microstrip narrowband BPF are investigated prior realization by varying the physical parameters of SRR including the width of rings and the gap between rings. From the experimental characterization, it shows that the realized microstrip narrowband BPF has a center frequency of 9.02 GHz with the values of return loss and insertion loss of 15.231 dB and 2.768 dB, respectively. The measured result is 20MHz lower than the simulated one which has center frequency of 9 GHz with the values of return loss and insertion loss of 15.025 dB and 2.242 dB, respectively.
Enhanced Modelling and Performance in Braided Pneumatic Muscle Actuators
(2003)

Pneumatic technology has been successfully applied for over two millennia. Even today, pneumatic cylinder based technology forms the keystone of many manufacturing processes where there is a need for simple, high-speed, low-cost, reliable motion. But when the system requires accurate control of position, velocity or acceleration profiles, these actuators form a far from satisfactory solution. Braided pneumatic muscle actuators (pMAs) form an interesting development of the pneumatic principle offering even higher power/weight performance, operation in a wide range of environments and accurate control of position, motion and force. This technology provides an interesting and potentially very successful alternative actuation source for robots as well as other applications. However, there are difficulties with this approach due to the following. (i) Modeling errors. Models of the force response are still nonoptimal and for good results these models are highly complex, which makes accurate design difficult. (ii) Low bandwidth—the bandwidth of the actuator—link assemblies are often considered to be too low for practical success in many applications, particularly robotics. In this paper we address these limitations and show how the performance in each area can be enhanced with overall improvements in the response and utility of the braided pMAs. KEY WORDS—actuators, braided pneumatic muscle actuators, McKibben muscles
High Dimensional Semiparametric Gaussian Copula Graphical Models
(2012)

We propose a semiparametric approach called the nonparanormal SKEPTIC for efficiently and robustly estimating high-dimensional undirected graphical models. To achieve modeling flexibility, we consider the nonparanormal graphical models proposed by Liu, Lafferty and Wasserman [J. Mach. Learn. Res. 10 (2009) 2295–2328]. To achieve estimation robustness, we exploit nonparametric rank-based correlation coefficient estimators, including Spearman’s rho and Kendall’s tau. We prove that the nonparanormal SKEPTIC achieves the optimal parametric rates of convergence for both graph recovery and parameter estimation. This result suggests that the nonparanormal graphical models can be used as a safe replacement of the popular Gaussian graphical models, even when the data are truly Gaussian. Besides theoretical analysis, we also conduct thorough numerical simulations to compare the graph recovery performance of different estimators under both ideal and noisy settings. The proposed methods are then applied on a large-scale genomic data set to illustrate their empirical usefulness. The R package huge implementing the proposed methods is available on the Comprehensive R Archive Network: http://cran.r-project.org/.